Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations471717
Missing cells879068
Missing cells (%)10.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.8 MiB
Average record size in memory144.0 B

Variable types

DateTime1
Numeric17

Alerts

aire_cupula_bt is highly overall correlated with peso_bt and 2 other fieldsHigh correlation
aire_sparger_bt is highly overall correlated with ph_cultivo_bt and 2 other fieldsHigh correlation
peso_bt is highly overall correlated with aire_cupula_bt and 2 other fieldsHigh correlation
ph_cultivo_bt is highly overall correlated with aire_sparger_bt and 2 other fieldsHigh correlation
pres_bio_bt is highly overall correlated with peso_btHigh correlation
pres_par_O2_1_bt is highly overall correlated with aire_cupula_bt and 4 other fieldsHigh correlation
pres_parcial_O2_bt is highly overall correlated with aire_sparger_bt and 2 other fieldsHigh correlation
total_antiespumante_bt is highly overall correlated with total_sol_base_btHigh correlation
total_sol_base_bt is highly overall correlated with total_antiespumante_btHigh correlation
vel_agitacion_bt is highly overall correlated with aire_cupula_bt and 2 other fieldsHigh correlation
vel_agitacion_bt has 39840 (8.4%) missing valuesMissing
aire_sparger_bt has 39840 (8.4%) missing valuesMissing
pres_bio_bt has 39827 (8.4%) missing valuesMissing
pres_par_O2_1_bt has 87715 (18.6%) missing valuesMissing
pres_par_O2_2_bt has 226371 (48.0%) missing valuesMissing
aire_cupula_bt has 39838 (8.4%) missing valuesMissing
peso_bt has 39829 (8.4%) missing valuesMissing
ph_1_bt has 44959 (9.5%) missing valuesMissing
ph_2_bt has 41993 (8.9%) missing valuesMissing
antiespumante_bt has 39839 (8.4%) missing valuesMissing
total_antiespumante_bt has 39832 (8.4%) missing valuesMissing
sol_base_bt has 39839 (8.4%) missing valuesMissing
total_sol_base_bt has 39833 (8.4%) missing valuesMissing
pres_parcial_O2_bt has 39837 (8.4%) missing valuesMissing
ph_cultivo_bt has 39840 (8.4%) missing valuesMissing
temp_bt has 39836 (8.4%) missing valuesMissing
ph_1_bt is highly skewed (γ1 = -99.57291661)Skewed
vel_agitacion_bt has 212983 (45.2%) zerosZeros
aire_sparger_bt has 364359 (77.2%) zerosZeros
pres_par_O2_1_bt has 280302 (59.4%) zerosZeros
pres_par_O2_2_bt has 185717 (39.4%) zerosZeros
aire_cupula_bt has 174461 (37.0%) zerosZeros
peso_bt has 70934 (15.0%) zerosZeros
antiespumante_bt has 385309 (81.7%) zerosZeros
total_antiespumante_bt has 60410 (12.8%) zerosZeros
sol_base_bt has 402514 (85.3%) zerosZeros
total_sol_base_bt has 176605 (37.4%) zerosZeros
ph_cultivo_bt has 44084 (9.3%) zerosZeros
temp_bt has 25125 (5.3%) zerosZeros

Reproduction

Analysis started2024-10-12 18:09:45.494398
Analysis finished2024-10-12 18:10:24.464139
Duration38.97 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

f_h_bt
Date

Distinct52413
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
Minimum2023-03-14 23:00:00+00:00
Maximum2024-09-10 22:00:00+00:00
2024-10-12T20:10:24.520638image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:24.599582image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

vel_agitacion_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct29312
Distinct (%)6.8%
Missing39840
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean22.264953
Minimum0
Maximum84
Zeros212983
Zeros (%)45.2%
Negative0
Negative (%)0.0%
Memory size3.6 MiB
2024-10-12T20:10:24.690051image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.1440002
Q329.656006
95-th percentile80
Maximum84
Range84
Interquartile range (IQR)29.656006

Descriptive statistics

Standard deviation29.388784
Coefficient of variation (CV)1.3199571
Kurtosis-0.34932571
Mean22.264953
Median Absolute Deviation (MAD)6.1440002
Skewness1.0974854
Sum9615721.3
Variance863.70063
MonotonicityNot monotonic
2024-10-12T20:10:24.775481image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 212983
45.2%
20 60132
 
12.7%
80 57343
 
12.2%
72 22049
 
4.7%
44 8447
 
1.8%
36 7381
 
1.6%
29.60799561 1552
 
0.3%
29.59200439 1548
 
0.3%
40 1507
 
0.3%
29.63199463 1057
 
0.2%
Other values (29302) 57878
 
12.3%
(Missing) 39840
 
8.4%
ValueCountFrequency (%)
0 212983
45.2%
2.879998779 1
 
< 0.1%
3.032000732 1
 
< 0.1%
3.088000488 1
 
< 0.1%
3.096002197 1
 
< 0.1%
3.111999512 2
 
< 0.1%
3.12800293 5
 
< 0.1%
3.128008392 1
 
< 0.1%
3.128163024 1
 
< 0.1%
3.12816351 1
 
< 0.1%
ValueCountFrequency (%)
84 274
 
0.1%
80 57343
12.2%
79.99999067 1
 
< 0.1%
79.99995117 1
 
< 0.1%
79.99991745 1
 
< 0.1%
79.99990776 1
 
< 0.1%
79.99987793 2
 
< 0.1%
79.99984741 1
 
< 0.1%
79.99980469 1
 
< 0.1%
79.99977417 1
 
< 0.1%

aire_sparger_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct21943
Distinct (%)5.1%
Missing39840
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean67.826063
Minimum-794.33599
Maximum805.696
Zeros364359
Zeros (%)77.2%
Negative40
Negative (%)< 0.1%
Memory size3.6 MiB
2024-10-12T20:10:24.843942image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-794.33599
5-th percentile0
Q10
median0
Q30
95-th percentile799.896
Maximum805.696
Range1600.032
Interquartile range (IQR)0

Descriptive statistics

Standard deviation220.13078
Coefficient of variation (CV)3.245519
Kurtosis7.1406655
Mean67.826063
Median Absolute Deviation (MAD)0
Skewness3.0199209
Sum29292517
Variance48457.559
MonotonicityNot monotonic
2024-10-12T20:10:24.919395image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 364359
77.2%
799.9199707 4669
 
1.0%
799.7919922 3854
 
0.8%
799.8959961 3390
 
0.7%
799.9040039 2359
 
0.5%
799.9439941 1929
 
0.4%
799.8640137 1877
 
0.4%
799.952002 1611
 
0.3%
799.8799805 1506
 
0.3%
799.9120117 1322
 
0.3%
Other values (21933) 45001
 
9.5%
(Missing) 39840
 
8.4%
ValueCountFrequency (%)
-794.3359863 1
 
< 0.1%
-788.3519531 1
 
< 0.1%
-0.2719997406 1
 
< 0.1%
-0.263999939 1
 
< 0.1%
-0.2240001678 1
 
< 0.1%
-0.2 5
< 0.1%
-0.1759998322 1
 
< 0.1%
-0.1680000305 1
 
< 0.1%
-0.1279998779 2
 
< 0.1%
-0.1119998932 3
< 0.1%
ValueCountFrequency (%)
805.6959961 455
 
0.1%
802.4080078 537
0.1%
801.752002 109
 
< 0.1%
800.1199707 786
0.2%
800.0640137 1216
0.3%
800.0560059 1317
0.3%
800.0239746 1007
0.2%
800.0080078 1126
0.2%
799.9919922 456
 
0.1%
799.9759766 461
 
0.1%

pres_bio_bt
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct182146
Distinct (%)42.2%
Missing39827
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean231.58039
Minimum-17.678558
Maximum815.40313
Zeros2587
Zeros (%)0.5%
Negative156125
Negative (%)33.1%
Memory size3.6 MiB
2024-10-12T20:10:24.997004image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-17.678558
5-th percentile-2.0994725
Q1-0.60184937
median2.2719344
Q3480
95-th percentile753.85596
Maximum815.40313
Range833.08168
Interquartile range (IQR)480.60185

Descriptive statistics

Standard deviation273.78591
Coefficient of variation (CV)1.18225
Kurtosis-1.2819045
Mean231.58039
Median Absolute Deviation (MAD)4.5898274
Skewness0.52666974
Sum1.0001725 × 108
Variance74958.724
MonotonicityNot monotonic
2024-10-12T20:10:25.071640image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
480 150719
32.0%
799.9919922 20256
 
4.3%
659.7328125 3794
 
0.8%
0 2587
 
0.5%
753.855957 2179
 
0.5%
693.7148926 1279
 
0.3%
640.9678711 1248
 
0.3%
716.7102539 1235
 
0.3%
-0.7841430664 1130
 
0.2%
-0.7638916016 918
 
0.2%
Other values (182136) 246545
52.3%
(Missing) 39827
 
8.4%
ValueCountFrequency (%)
-17.67855826 1
< 0.1%
-17.46685468 1
< 0.1%
-17.40801237 1
< 0.1%
-17.40423101 1
< 0.1%
-17.40284387 1
< 0.1%
-17.39293823 1
< 0.1%
-17.38617579 1
< 0.1%
-17.36105496 1
< 0.1%
-17.36061863 1
< 0.1%
-17.33317647 1
< 0.1%
ValueCountFrequency (%)
815.403125 189
 
< 0.1%
812.6696289 138
 
< 0.1%
799.9919922 20256
4.3%
799.8291548 1
 
< 0.1%
799.391338 1
 
< 0.1%
799.278426 1
 
< 0.1%
799.077949 1
 
< 0.1%
787.4319824 1
 
< 0.1%
777.5439941 1
 
< 0.1%
775.8 1
 
< 0.1%

pres_par_O2_1_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct50890
Distinct (%)13.3%
Missing87715
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean460.67193
Minimum-0.28136597
Maximum12268.625
Zeros280302
Zeros (%)59.4%
Negative9263
Negative (%)2.0%
Memory size3.6 MiB
2024-10-12T20:10:25.163717image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.28136597
5-th percentile0
Q10
median0
Q30
95-th percentile5668.0852
Maximum12268.625
Range12268.906
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1750.3644
Coefficient of variation (CV)3.79959
Kurtosis13.964581
Mean460.67193
Median Absolute Deviation (MAD)0
Skewness3.9001034
Sum1.7689894 × 108
Variance3063775.7
MonotonicityNot monotonic
2024-10-12T20:10:25.259237image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 280302
59.4%
-0.2813659668 9254
 
2.0%
9120.979687 3790
 
0.8%
6505.707813 2181
 
0.5%
5668.085156 1629
 
0.3%
248.8854736 1337
 
0.3%
7370.183594 1328
 
0.3%
6996.889844 1285
 
0.3%
167.4596191 1049
 
0.2%
7987.819531 1033
 
0.2%
Other values (50880) 80814
 
17.1%
(Missing) 87715
 
18.6%
ValueCountFrequency (%)
-0.2813659668 9254
2.0%
-0.2218725676 1
 
< 0.1%
-0.1898950697 1
 
< 0.1%
-0.1892120976 1
 
< 0.1%
-0.1504498587 1
 
< 0.1%
-0.1471444051 1
 
< 0.1%
-0.1356840012 1
 
< 0.1%
-0.09656236762 1
 
< 0.1%
-0.09238882492 1
 
< 0.1%
-0.0571876545 1
 
< 0.1%
ValueCountFrequency (%)
12268.625 41
< 0.1%
12235.15078 1
 
< 0.1%
12200.79766 1
 
< 0.1%
12138.02578 1
 
< 0.1%
12083.57969 1
 
< 0.1%
12013.67734 32
< 0.1%
12013.36273 1
 
< 0.1%
12002.17031 2
 
< 0.1%
11992.73203 1
 
< 0.1%
11976.50078 1
 
< 0.1%

pres_par_O2_2_bt
Real number (ℝ)

MISSING  ZEROS 

Distinct10147
Distinct (%)4.1%
Missing226371
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean0.76295263
Minimum-0.0076965332
Maximum89.740161
Zeros185717
Zeros (%)39.4%
Negative47902
Negative (%)10.2%
Memory size3.6 MiB
2024-10-12T20:10:25.335389image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.0076965332
5-th percentile-0.0055297852
Q10
median0
Q30
95-th percentile0
Maximum89.740161
Range89.747858
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.5391698
Coefficient of variation (CV)7.2601751
Kurtosis123.56108
Mean0.76295263
Median Absolute Deviation (MAD)0
Skewness10.407117
Sum187187.38
Variance30.682402
MonotonicityNot monotonic
2024-10-12T20:10:25.407800image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 185717
39.4%
-0.005529785156 46981
 
10.0%
-0.007696533203 727
 
0.2%
8 585
 
0.1%
78.38275757 20
 
< 0.1%
79.12711792 15
 
< 0.1%
78.82723389 13
 
< 0.1%
7.610464478 13
 
< 0.1%
28.45993042 12
 
< 0.1%
78.68264771 12
 
< 0.1%
Other values (10137) 11251
 
2.4%
(Missing) 226371
48.0%
ValueCountFrequency (%)
-0.007696533203 727
 
0.2%
-0.005529785156 46981
10.0%
-0.005525782548 1
 
< 0.1%
-0.005519367462 1
 
< 0.1%
-0.005519161521 1
 
< 0.1%
-0.005514969802 1
 
< 0.1%
-0.005509946854 1
 
< 0.1%
-0.005508064171 1
 
< 0.1%
-0.005506218395 1
 
< 0.1%
-0.005506047471 1
 
< 0.1%
ValueCountFrequency (%)
89.74016113 4
< 0.1%
89.73720789 1
 
< 0.1%
89.65920385 1
 
< 0.1%
89.63708413 1
 
< 0.1%
89.61322148 1
 
< 0.1%
89.59118919 1
 
< 0.1%
89.58363173 1
 
< 0.1%
89.58114014 9
< 0.1%
89.47863892 1
 
< 0.1%
89.42779541 6
< 0.1%

aire_cupula_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct213252
Distinct (%)49.4%
Missing39838
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean4.7613908
Minimum0
Maximum157.07986
Zeros174461
Zeros (%)37.0%
Negative0
Negative (%)0.0%
Memory size3.6 MiB
2024-10-12T20:10:25.476993image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.9997629
Q34.0001707
95-th percentile21.119997
Maximum157.07986
Range157.07986
Interquartile range (IQR)4.0001707

Descriptive statistics

Standard deviation9.9105443
Coefficient of variation (CV)2.081439
Kurtosis34.037114
Mean4.7613908
Median Absolute Deviation (MAD)3.9997629
Skewness5.13954
Sum2056344.7
Variance98.218888
MonotonicityNot monotonic
2024-10-12T20:10:25.553483image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 174461
37.0%
40.47999878 3812
 
0.8%
21.11999664 3547
 
0.8%
6.6 3498
 
0.7%
22.43999634 2441
 
0.5%
17.15999756 2083
 
0.4%
11.87999878 1999
 
0.4%
5.279999924 1912
 
0.4%
26.39999695 1864
 
0.4%
28.16000366 1375
 
0.3%
Other values (213242) 234887
49.8%
(Missing) 39838
 
8.4%
ValueCountFrequency (%)
0 174461
37.0%
0.01962204832 1
 
< 0.1%
0.02326878684 1
 
< 0.1%
0.07128547617 1
 
< 0.1%
0.1315726093 1
 
< 0.1%
0.1423443709 1
 
< 0.1%
0.1841951646 1
 
< 0.1%
0.2217831827 1
 
< 0.1%
0.3634535565 1
 
< 0.1%
0.3980566611 1
 
< 0.1%
ValueCountFrequency (%)
157.0798584 1
 
< 0.1%
100.7599487 211
 
< 0.1%
97.68005981 410
0.1%
96.79995117 745
0.2%
88.44005127 17
 
< 0.1%
81.84004517 42
 
< 0.1%
81.39996948 17
 
< 0.1%
80.95997314 93
 
< 0.1%
79.63997803 80
 
< 0.1%
77.8800415 19
 
< 0.1%

peso_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct29717
Distinct (%)6.9%
Missing39829
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean398.10617
Minimum-84.4
Maximum1732.4
Zeros70934
Zeros (%)15.0%
Negative147770
Negative (%)31.3%
Memory size3.6 MiB
2024-10-12T20:10:25.632640image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-84.4
5-th percentile-18.4
Q1-6
median0
Q3170.64
95-th percentile1656
Maximum1732.4
Range1816.8
Interquartile range (IQR)176.64

Descriptive statistics

Standard deviation667.90672
Coefficient of variation (CV)1.67771
Kurtosis-0.42299138
Mean398.10617
Median Absolute Deviation (MAD)18
Skewness1.231598
Sum1.7193728 × 108
Variance446099.39
MonotonicityNot monotonic
2024-10-12T20:10:25.717570image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 70934
 
15.0%
-18 15353
 
3.3%
-1.2 10058
 
2.1%
0.4 8174
 
1.7%
-18.4 7815
 
1.7%
-17.6 7179
 
1.5%
-17.2 5905
 
1.3%
-19.2 5475
 
1.2%
-6.8 4593
 
1.0%
-6.959999847 4335
 
0.9%
Other values (29707) 292067
61.9%
(Missing) 39829
 
8.4%
ValueCountFrequency (%)
-84.4 91
< 0.1%
-84.08163405 1
 
< 0.1%
-84.07962254 1
 
< 0.1%
-84 36
 
< 0.1%
-70.4 1
 
< 0.1%
-70 1
 
< 0.1%
-69.77818471 1
 
< 0.1%
-69.6 1
 
< 0.1%
-68 17
 
< 0.1%
-67.6 78
< 0.1%
ValueCountFrequency (%)
1732.4 3
 
< 0.1%
1732 1
 
< 0.1%
1720.4 1
 
< 0.1%
1718 6
 
< 0.1%
1717.6 14
 
< 0.1%
1717.2 15
 
< 0.1%
1716.8 27
< 0.1%
1716.4 36
< 0.1%
1716.211284 1
 
< 0.1%
1716 64
< 0.1%

ph_1_bt
Real number (ℝ)

MISSING  SKEWED 

Distinct50417
Distinct (%)11.8%
Missing44959
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean-1.4290232
Minimum-16705.317
Maximum2049.6152
Zeros174
Zeros (%)< 0.1%
Negative50531
Negative (%)10.7%
Memory size3.6 MiB
2024-10-12T20:10:25.790185image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-16705.317
5-th percentile-4.6862289
Q11.5124306
median1.7072765
Q35.8725303
95-th percentile6.2720001
Maximum2049.6152
Range18754.932
Interquartile range (IQR)4.3600998

Descriptive statistics

Standard deviation142.28843
Coefficient of variation (CV)-99.570415
Kurtosis11636.234
Mean-1.4290232
Median Absolute Deviation (MAD)1.9420391
Skewness-99.572917
Sum-609847.09
Variance20245.999
MonotonicityNot monotonic
2024-10-12T20:10:25.880357image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.272000122 23841
 
5.1%
-4.686228943 22828
 
4.8%
-0.2347625732 18573
 
3.9%
1.707276535 13834
 
2.9%
4.539850616 4451
 
0.9%
-0.1569252014 3568
 
0.8%
-527.3871582 3315
 
0.7%
1.587190247 3254
 
0.7%
1.305897903 3115
 
0.7%
1.630574226 3078
 
0.7%
Other values (50407) 326901
69.3%
(Missing) 44959
 
9.5%
ValueCountFrequency (%)
-16705.31719 26
 
< 0.1%
-10298.18984 1
 
< 0.1%
-527.3871582 3315
0.7%
-526.3940933 1
 
< 0.1%
-526.1155903 1
 
< 0.1%
-525.0820986 1
 
< 0.1%
-516.1368823 1
 
< 0.1%
-515.2058735 1
 
< 0.1%
-191.6294922 1
 
< 0.1%
-8.040552655 1
 
< 0.1%
ValueCountFrequency (%)
2049.615234 1
 
< 0.1%
1950.344922 1
 
< 0.1%
1883.366797 1
 
< 0.1%
1687.218359 1
 
< 0.1%
1554.458887 1
 
< 0.1%
1389.407324 1
 
< 0.1%
1357.113574 1
 
< 0.1%
1355.918262 1
 
< 0.1%
1344.499091 1
 
< 0.1%
1059.302637 4
< 0.1%

ph_2_bt
Real number (ℝ)

MISSING 

Distinct15484
Distinct (%)3.6%
Missing41993
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean-24.918618
Minimum-389.26096
Maximum178.7813
Zeros276
Zeros (%)0.1%
Negative215057
Negative (%)45.6%
Memory size3.6 MiB
2024-10-12T20:10:25.992394image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-389.26096
5-th percentile-389.26096
Q1-0.2552742
median-0.011331558
Q32.5092309
95-th percentile5.879974
Maximum178.7813
Range568.04226
Interquartile range (IQR)2.7645051

Descriptive statistics

Standard deviation92.918234
Coefficient of variation (CV)-3.7288678
Kurtosis11.278267
Mean-24.918618
Median Absolute Deviation (MAD)1.357432
Skewness-3.620123
Sum-10708128
Variance8633.7982
MonotonicityNot monotonic
2024-10-12T20:10:26.368892image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.2 64036
13.6%
-0.01133155823 46432
 
9.8%
-0.2552742004 42468
 
9.0%
-38.21071167 28873
 
6.1%
1.242311668 26562
 
5.6%
-389.2609619 25933
 
5.5%
1.300272942 22903
 
4.9%
-1.969050598 19862
 
4.2%
-0.8517827988 19006
 
4.0%
-0.1385864258 16902
 
3.6%
Other values (15474) 116747
24.7%
(Missing) 41993
 
8.9%
ValueCountFrequency (%)
-389.2609619 25933
5.5%
-389.1811626 1
 
< 0.1%
-387.8849362 1
 
< 0.1%
-385.6619304 1
 
< 0.1%
-385.3407178 1
 
< 0.1%
-379.1654863 1
 
< 0.1%
-377.7421594 1
 
< 0.1%
-336.5587212 1
 
< 0.1%
-333.4207645 1
 
< 0.1%
-314.0435053 1
 
< 0.1%
ValueCountFrequency (%)
178.7812988 4
 
< 0.1%
178.1812988 1
 
< 0.1%
175.8241699 1
 
< 0.1%
158.660083 1
 
< 0.1%
38.09625549 1
 
< 0.1%
11.98619843 1
 
< 0.1%
10.34707794 27
< 0.1%
10.33210297 1
 
< 0.1%
10.26894531 1
 
< 0.1%
10.19732208 1
 
< 0.1%

antiespumante_bt
Real number (ℝ)

MISSING  ZEROS 

Distinct2019
Distinct (%)0.5%
Missing39839
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean82.530459
Minimum-22.4
Maximum1711.4491
Zeros385309
Zeros (%)81.7%
Negative19766
Negative (%)4.2%
Memory size3.6 MiB
2024-10-12T20:10:26.441991image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-22.4
5-th percentile0
Q10
median0
Q30
95-th percentile1526.4
Maximum1711.4491
Range1733.8491
Interquartile range (IQR)0

Descriptive statistics

Standard deviation354.48992
Coefficient of variation (CV)4.2952616
Kurtosis14.579148
Mean82.530459
Median Absolute Deviation (MAD)0
Skewness4.0634558
Sum35643090
Variance125663.1
MonotonicityNot monotonic
2024-10-12T20:10:26.515605image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 385309
81.7%
-18 2867
 
0.6%
-18.4 2528
 
0.5%
-14.4 2126
 
0.5%
-17.2 2017
 
0.4%
-17.6 1763
 
0.4%
-18.8 1542
 
0.3%
-0.4 1302
 
0.3%
-1.6 1247
 
0.3%
2 762
 
0.2%
Other values (2009) 30415
 
6.4%
(Missing) 39839
 
8.4%
ValueCountFrequency (%)
-22.4 2
 
< 0.1%
-22 3
 
< 0.1%
-21.6 4
 
< 0.1%
-21.2 10
 
< 0.1%
-20.8 16
 
< 0.1%
-20.4 23
 
< 0.1%
-20 28
 
< 0.1%
-19.68075124 1
 
< 0.1%
-19.6 47
 
< 0.1%
-19.2 611
0.1%
ValueCountFrequency (%)
1711.449056 1
 
< 0.1%
1710.587867 1
 
< 0.1%
1706.719481 1
 
< 0.1%
1706 17
< 0.1%
1705.6 25
< 0.1%
1705.591693 1
 
< 0.1%
1705.505852 1
 
< 0.1%
1705.457903 1
 
< 0.1%
1705.2 31
< 0.1%
1705.058271 1
 
< 0.1%

total_antiespumante_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct35087
Distinct (%)8.1%
Missing39832
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean40.102418
Minimum0
Maximum8199.6
Zeros60410
Zeros (%)12.8%
Negative0
Negative (%)0.0%
Memory size3.6 MiB
2024-10-12T20:10:26.589649image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.9599998
median14.88
Q340.8
95-th percentile126.48002
Maximum8199.6
Range8199.6
Interquartile range (IQR)35.84

Descriptive statistics

Standard deviation138.60133
Coefficient of variation (CV)3.4561838
Kurtosis363.77702
Mean40.102418
Median Absolute Deviation (MAD)10.880476
Skewness16.050576
Sum17319633
Variance19210.328
MonotonicityNot monotonic
2024-10-12T20:10:26.656946image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60410
 
12.8%
9.919999695 30184
 
6.4%
7.43999939 28946
 
6.1%
14.88000031 19846
 
4.2%
17.36000061 19360
 
4.1%
12.4 19128
 
4.1%
49.59999084 16601
 
3.5%
4.959999847 13138
 
2.8%
24.80000153 9760
 
2.1%
59.51998901 8257
 
1.8%
Other values (35077) 206255
43.7%
(Missing) 39832
 
8.4%
ValueCountFrequency (%)
0 60410
12.8%
0.002796132197 1
 
< 0.1%
0.004837127198 1
 
< 0.1%
0.00974709501 1
 
< 0.1%
0.01114275186 1
 
< 0.1%
0.01336322829 1
 
< 0.1%
0.01440595995 1
 
< 0.1%
0.01606404052 1
 
< 0.1%
0.01717965255 1
 
< 0.1%
0.01790767497 1
 
< 0.1%
ValueCountFrequency (%)
8199.6 2
 
< 0.1%
7966.627657 1
 
< 0.1%
6886.6272 1
 
< 0.1%
5806.628343 1
 
< 0.1%
4726.6272 1
 
< 0.1%
3646.628057 1
 
< 0.1%
2987.585547 479
0.1%
2820.466423 1
 
< 0.1%
2656.748096 1
 
< 0.1%
2647.073145 1
 
< 0.1%

sol_base_bt
Real number (ℝ)

MISSING  ZEROS 

Distinct26880
Distinct (%)6.2%
Missing39839
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean0.2396154
Minimum0
Maximum80
Zeros402514
Zeros (%)85.3%
Negative0
Negative (%)0.0%
Memory size3.6 MiB
2024-10-12T20:10:26.726996image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.91884852
Maximum80
Range80
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1916776
Coefficient of variation (CV)4.9732928
Kurtosis198.06249
Mean0.2396154
Median Absolute Deviation (MAD)0
Skewness8.4134001
Sum103484.62
Variance1.4200954
MonotonicityNot monotonic
2024-10-12T20:10:26.809532image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 402514
85.3%
8 2185
 
0.5%
7.610464478 37
 
< 0.1%
2.400146484 18
 
< 0.1%
7.609883881 17
 
< 0.1%
7.200439453 15
 
< 0.1%
2.399963379 15
 
< 0.1%
4.799926758 14
 
< 0.1%
48 14
 
< 0.1%
4.800292969 13
 
< 0.1%
Other values (26870) 27036
 
5.7%
(Missing) 39839
 
8.4%
ValueCountFrequency (%)
0 402514
85.3%
3.051757858 × 10-71
 
< 0.1%
8.585711509 × 10-71
 
< 0.1%
3.277489783 × 10-61
 
< 0.1%
4.588888731 × 10-61
 
< 0.1%
1.266804469 × 10-51
 
< 0.1%
2.228564413 × 10-51
 
< 0.1%
2.31698436 × 10-51
 
< 0.1%
2.376482648 × 10-51
 
< 0.1%
2.86196768 × 10-51
 
< 0.1%
ValueCountFrequency (%)
80 1
 
< 0.1%
72 1
 
< 0.1%
48 14
< 0.1%
46.86744091 1
 
< 0.1%
45.76459981 1
 
< 0.1%
32.52447157 1
 
< 0.1%
28.69340853 1
 
< 0.1%
27.79323548 1
 
< 0.1%
20.06333269 1
 
< 0.1%
14.11384463 1
 
< 0.1%

total_sol_base_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct46979
Distinct (%)10.9%
Missing39833
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean2146.3373
Minimum0
Maximum22260.513
Zeros176605
Zeros (%)37.4%
Negative0
Negative (%)0.0%
Memory size3.6 MiB
2024-10-12T20:10:26.884120image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median23.901222
Q34386.6762
95-th percentile8224.4727
Maximum22260.513
Range22260.513
Interquartile range (IQR)4386.6762

Descriptive statistics

Standard deviation3285.6851
Coefficient of variation (CV)1.5308335
Kurtosis2.1249031
Mean2146.3373
Median Absolute Deviation (MAD)23.901222
Skewness1.5016318
Sum9.2696875 × 108
Variance10795726
MonotonicityNot monotonic
2024-10-12T20:10:26.954832image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 176605
37.4%
2014.737695 14386
 
3.0%
7684.094531 4559
 
1.0%
11393.56953 4070
 
0.9%
8099.764844 3942
 
0.8%
11.8683548 3770
 
0.8%
14.3049881 3726
 
0.8%
62.8109314 3386
 
0.7%
4386.676172 3250
 
0.7%
6431.4 2980
 
0.6%
Other values (46969) 211210
44.8%
(Missing) 39833
 
8.4%
ValueCountFrequency (%)
0 176605
37.4%
0.01666003704 1
 
< 0.1%
0.0167649371 1
 
< 0.1%
0.01684833063 1
 
< 0.1%
0.03293879197 1
 
< 0.1%
0.03316664088 1
 
< 0.1%
0.03615813777 1
 
< 0.1%
0.0439114691 1
 
< 0.1%
0.0715862416 1
 
< 0.1%
0.08394892034 1
 
< 0.1%
ValueCountFrequency (%)
22260.5125 1
 
< 0.1%
22105.09613 1
 
< 0.1%
21906.81499 1
 
< 0.1%
21708.53363 1
 
< 0.1%
21510.25238 1
 
< 0.1%
21311.5077 1
 
< 0.1%
21113.68988 1
 
< 0.1%
21070.66875 852
0.2%
21016.14219 1
 
< 0.1%
20983.20625 1
 
< 0.1%

pres_parcial_O2_bt
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct85855
Distinct (%)19.9%
Missing39837
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean797.81382
Minimum-14.840857
Maximum32921.481
Zeros136
Zeros (%)< 0.1%
Negative19534
Negative (%)4.1%
Memory size3.6 MiB
2024-10-12T20:10:27.028106image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-14.840857
5-th percentile0.17705969
Q1480
median741.76357
Q3799.99199
95-th percentile809.7085
Maximum32921.481
Range32936.322
Interquartile range (IQR)319.99199

Descriptive statistics

Standard deviation2630.5987
Coefficient of variation (CV)3.2972589
Kurtosis142.99772
Mean797.81382
Median Absolute Deviation (MAD)58.228418
Skewness11.949902
Sum3.4455983 × 108
Variance6920049.6
MonotonicityNot monotonic
2024-10-12T20:10:27.101717image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
799.9919922 174271
36.9%
480 14851
 
3.1%
734.0049805 4572
 
1.0%
703.9084473 4072
 
0.9%
710.0310547 3947
 
0.8%
809.7084961 3731
 
0.8%
712.9417969 3648
 
0.8%
861.6889648 3318
 
0.7%
731.789209 3179
 
0.7%
741.7635742 2869
 
0.6%
Other values (85845) 213422
45.2%
(Missing) 39837
 
8.4%
ValueCountFrequency (%)
-14.84085693 1
< 0.1%
-10.546875 1
< 0.1%
-10.46581812 1
< 0.1%
-10.46541518 1
< 0.1%
-10.40535583 1
< 0.1%
-10.38617345 1
< 0.1%
-10.38502773 1
< 0.1%
-10.22196953 1
< 0.1%
-10.20229146 1
< 0.1%
-10.18298932 1
< 0.1%
ValueCountFrequency (%)
32921.48125 2835
0.6%
26400.29596 1
 
< 0.1%
943.9433594 777
 
0.2%
917.7376953 196
 
< 0.1%
916.7911133 110
 
< 0.1%
916.6861328 668
 
0.1%
905.0707031 607
 
0.1%
898.8673828 95
 
< 0.1%
883.7032722 1
 
< 0.1%
880.4666016 21
 
< 0.1%

ph_cultivo_bt
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13382
Distinct (%)3.1%
Missing39840
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean543.93011
Minimum-794.36797
Maximum805.952
Zeros44084
Zeros (%)9.3%
Negative3885
Negative (%)0.8%
Memory size3.6 MiB
2024-10-12T20:10:27.197817image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-794.36797
5-th percentile0
Q15.8959961
median799.91201
Q3800.03999
95-th percentile800.40801
Maximum805.952
Range1600.32
Interquartile range (IQR)794.14399

Descriptive statistics

Standard deviation381.34661
Coefficient of variation (CV)0.70109488
Kurtosis-0.74930803
Mean543.93011
Median Absolute Deviation (MAD)0.22397461
Skewness-0.91924717
Sum2.349109 × 108
Variance145425.24
MonotonicityNot monotonic
2024-10-12T20:10:27.282099image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44084
 
9.3%
800.0399902 19363
 
4.1%
799.9120117 12013
 
2.5%
799.9600098 9253
 
2.0%
800.3040039 8433
 
1.8%
799.9919922 8326
 
1.8%
800 8147
 
1.7%
799.9439941 8082
 
1.7%
799.8640137 7899
 
1.7%
799.9679688 7519
 
1.6%
Other values (13372) 298758
63.3%
(Missing) 39840
 
8.4%
ValueCountFrequency (%)
-794.3679688 121
< 0.1%
-794.2719727 1
 
< 0.1%
-794.2239746 2
 
< 0.1%
-794.1839844 10
 
< 0.1%
-794.1359863 7
 
< 0.1%
-794.1120117 274
0.1%
-794.0959961 1
 
< 0.1%
-794.047998 1
 
< 0.1%
-793.8719727 1
 
< 0.1%
-793.8640137 2
 
< 0.1%
ValueCountFrequency (%)
805.952002 442
 
0.1%
805.7679688 469
 
0.1%
802.352002 664
 
0.1%
801.9359863 551
 
0.1%
800.7359863 817
 
0.2%
800.6959961 1610
0.3%
800.6 1708
0.4%
800.5759766 2177
0.5%
800.5199707 560
 
0.1%
800.5120117 1337
0.3%

temp_bt
Real number (ℝ)

MISSING  ZEROS 

Distinct218100
Distinct (%)50.5%
Missing39836
Missing (%)8.4%
Infinite0
Infinite (%)0.0%
Mean18.526823
Minimum-0.4
Maximum81.073239
Zeros25125
Zeros (%)5.3%
Negative2
Negative (%)< 0.1%
Memory size3.6 MiB
2024-10-12T20:10:27.361011image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.4
5-th percentile0
Q112.366531
median16.359578
Q323.992437
95-th percentile29.83653
Maximum81.073239
Range81.473239
Interquartile range (IQR)11.625906

Descriptive statistics

Standard deviation14.732128
Coefficient of variation (CV)0.79517833
Kurtosis8.0925512
Mean18.526823
Median Absolute Deviation (MAD)6.0555742
Skewness2.393024
Sum8001382.9
Variance217.0356
MonotonicityNot monotonic
2024-10-12T20:10:27.438475image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25125
 
5.3%
80 15079
 
3.2%
20 5433
 
1.2%
29.60799561 5118
 
1.1%
3.208001709 3621
 
0.8%
29.63199463 2866
 
0.6%
3.2 2695
 
0.6%
29.6 2139
 
0.5%
3.176000977 2067
 
0.4%
29.61600342 1925
 
0.4%
Other values (218090) 365813
77.5%
(Missing) 39836
 
8.4%
ValueCountFrequency (%)
-0.4 1
 
< 0.1%
-0.2479980469 1
 
< 0.1%
0 25125
5.3%
0.1342207533 1
 
< 0.1%
0.1572525757 1
 
< 0.1%
0.4239990234 1
 
< 0.1%
2.960000038 1
 
< 0.1%
2.976000977 1
 
< 0.1%
2.983999062 1
 
< 0.1%
2.984696145 1
 
< 0.1%
ValueCountFrequency (%)
81.07323879 1
 
< 0.1%
80.99927861 1
 
< 0.1%
80.96800537 1
 
< 0.1%
80.83199463 1
 
< 0.1%
80.64000244 1
 
< 0.1%
80.56978423 1
 
< 0.1%
80.23727531 1
 
< 0.1%
80.14399414 1
 
< 0.1%
80 15079
3.2%
79.90183953 1
 
< 0.1%

id_bio
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13973.556
Minimum13169
Maximum14618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 MiB
2024-10-12T20:10:27.507013image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum13169
5-th percentile13169
Q113171
median14614
Q314616
95-th percentile14618
Maximum14618
Range1449
Interquartile range (IQR)1445

Descriptive statistics

Standard deviation718.27665
Coefficient of variation (CV)0.051402568
Kurtosis-1.9499963
Mean13973.556
Median Absolute Deviation (MAD)4
Skewness-0.22360426
Sum6.5915637 × 109
Variance515921.34
MonotonicityIncreasing
2024-10-12T20:10:27.561575image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
13169 52413
11.1%
13170 52413
11.1%
13171 52413
11.1%
13172 52413
11.1%
14614 52413
11.1%
14615 52413
11.1%
14616 52413
11.1%
14617 52413
11.1%
14618 52413
11.1%
ValueCountFrequency (%)
13169 52413
11.1%
13170 52413
11.1%
13171 52413
11.1%
13172 52413
11.1%
14614 52413
11.1%
14615 52413
11.1%
14616 52413
11.1%
14617 52413
11.1%
14618 52413
11.1%
ValueCountFrequency (%)
14618 52413
11.1%
14617 52413
11.1%
14616 52413
11.1%
14615 52413
11.1%
14614 52413
11.1%
13172 52413
11.1%
13171 52413
11.1%
13170 52413
11.1%
13169 52413
11.1%

Interactions

2024-10-12T20:10:20.122728image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:54.198218image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:55.953026image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:09:58.905493image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:00.387110image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:01.727342image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:03.670222image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:05.336744image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:10:10.177220image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:10:13.591685image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:15.083225image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.651802image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:10:10.252341image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:12.041496image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:10:16.730888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:18.309862image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:20.433393image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:54.381122image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:10:10.335109image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:12.140056image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:13.761506image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:15.284697image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.818755image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:18.397551image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:20.569393image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:54.452826image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:56.211632image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:57.726778image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:10:00.611720image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-10-12T20:09:59.803583image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:01.235014image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:02.707218image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:04.652659image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:06.383489image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:08.023142image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:09.584618image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:11.123909image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:12.982472image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:14.521640image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.072744image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:17.647529image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:19.455147image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:22.017220image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:55.227711image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:56.984354image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:58.450323image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:59.903756image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:01.316848image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:02.809195image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:04.767200image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:06.479284image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:08.106745image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:09.682090image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:11.492685image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:13.098063image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:14.603464image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.173119image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:17.735591image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:19.546012image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:22.176171image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:55.315447image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:57.067370image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:58.534860image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:59.998413image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:01.382952image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:02.900656image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:04.860553image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:06.560052image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:08.185661image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:09.761915image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:11.566802image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:13.201129image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:14.679078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.252768image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:17.817907image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:19.650086image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:22.320640image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:55.404674image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:57.174673image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:58.610868image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:00.078007image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:01.469147image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:03.012677image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:04.963385image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:06.647319image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:08.267569image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:09.845251image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:11.653774image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:13.285798image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:14.760115image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.332878image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:17.900108image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:19.731999image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:22.469079image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:55.505962image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:57.278582image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:58.692935image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:00.184190image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:01.545188image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:03.105690image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:05.051673image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:06.737312image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:08.350185image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:09.931078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:11.741036image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:13.373242image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:14.844488image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.418221image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:17.987407image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:19.817026image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:22.702484image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:55.675231image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:57.426228image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:09:58.843683image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:00.331281image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:01.659351image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:03.302715image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:05.262546image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:06.901583image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:08.532289image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:10.087568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:11.892866image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:13.521747image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:15.001097image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:16.569967image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:18.155044image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-10-12T20:10:19.971440image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-10-12T20:10:27.632583image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
aire_cupula_btaire_sparger_btantiespumante_btid_biopeso_btph_1_btph_2_btph_cultivo_btpres_bio_btpres_par_O2_1_btpres_par_O2_2_btpres_parcial_O2_btsol_base_bttemp_bttotal_antiespumante_bttotal_sol_base_btvel_agitacion_bt
aire_cupula_bt1.0000.4910.0380.0080.5580.1480.121-0.411-0.3110.5280.100-0.2580.1520.032-0.418-0.4230.596
aire_sparger_bt0.4911.0000.0970.0890.073-0.0650.233-0.5640.3740.5890.239-0.5870.1520.073-0.332-0.1980.276
antiespumante_bt0.0380.0971.0000.020-0.0130.0600.102-0.057-0.016-0.0720.145-0.160-0.0140.420-0.0150.0330.072
id_bio0.0080.0890.0201.000-0.0220.1750.1590.0420.128-0.0710.0180.056-0.091-0.0120.004-0.076-0.030
peso_bt0.5580.073-0.013-0.0221.0000.440-0.098-0.209-0.6480.370-0.162-0.0840.4030.159-0.113-0.3360.819
ph_1_bt0.148-0.0650.0600.1750.4401.000-0.144-0.046-0.3170.147-0.093-0.0610.2430.1950.051-0.0800.441
ph_2_bt0.1210.2330.1020.159-0.098-0.1441.000-0.0160.1700.0930.289-0.122-0.1360.032-0.234-0.2840.018
ph_cultivo_bt-0.411-0.564-0.0570.042-0.209-0.046-0.0161.000-0.150-0.550-0.0540.640-0.256-0.1610.112-0.071-0.358
pres_bio_bt-0.3110.374-0.0160.128-0.648-0.3170.170-0.1501.0000.0860.210-0.336-0.1410.0520.0590.224-0.429
pres_par_O2_1_bt0.5280.589-0.072-0.0710.3700.1470.093-0.5500.0861.0000.220-0.6290.3850.270-0.251-0.1480.541
pres_par_O2_2_bt0.1000.2390.1450.018-0.162-0.0930.289-0.0540.2100.2201.000-0.167-0.1410.085-0.339-0.2450.050
pres_parcial_O2_bt-0.258-0.587-0.1600.056-0.084-0.061-0.1220.640-0.336-0.629-0.1671.000-0.329-0.3450.044-0.137-0.324
sol_base_bt0.1520.152-0.014-0.0910.4030.243-0.136-0.256-0.1410.385-0.141-0.3291.0000.3510.1330.1890.415
temp_bt0.0320.0730.420-0.0120.1590.1950.032-0.1610.0520.2700.085-0.3450.3511.0000.1040.2060.263
total_antiespumante_bt-0.418-0.332-0.0150.004-0.1130.051-0.2340.1120.059-0.251-0.3390.0440.1330.1041.0000.658-0.198
total_sol_base_bt-0.423-0.1980.033-0.076-0.336-0.080-0.284-0.0710.224-0.148-0.245-0.1370.1890.2060.6581.000-0.324
vel_agitacion_bt0.5960.2760.072-0.0300.8190.4410.018-0.358-0.4290.5410.050-0.3240.4150.263-0.198-0.3241.000

Missing values

2024-10-12T20:10:22.796156image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-12T20:10:23.183241image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-10-12T20:10:23.940009image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

f_h_btvel_agitacion_btaire_sparger_btpres_bio_btpres_par_O2_1_btpres_par_O2_2_btaire_cupula_btpeso_btph_1_btph_2_btantiespumante_bttotal_antiespumante_btsol_base_bttotal_sol_base_btpres_parcial_O2_btph_cultivo_bttemp_btid_bio
02023-03-14 23:00:00+00:000.00.0480.00.0NaN0.0-20.0000001.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.16352413169
12023-03-14 23:15:00+00:000.00.0480.00.0NaN0.0-17.3353881.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.10225613169
22023-03-14 23:30:00+00:000.00.0480.00.0NaN0.0-20.0359171.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.07025013169
32023-03-14 23:45:00+00:000.00.0480.00.0NaN0.0-20.2604541.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.00443013169
42023-03-15 00:00:00+00:000.00.0480.00.0NaN0.0-20.3991361.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.02043313169
52023-03-15 00:15:00+00:000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.027.2800020.01480.795851655.892432799.62397517.92449813169
62023-03-15 00:30:00+00:000.00.0480.00.0NaN0.0-17.8290691.56356-0.0113320.027.2800020.0361.983921655.892432799.62397517.92898713169
72023-03-15 00:45:00+00:000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.022.3400420.01486.330176655.892432799.62397517.94042813169
82023-03-15 01:00:00+00:000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.027.2800020.01486.330176655.892432799.62397517.84736013169
92023-03-15 01:15:00+00:000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.027.2800020.01486.330176655.892432799.62397517.71571813169
f_h_btvel_agitacion_btaire_sparger_btpres_bio_btpres_par_O2_1_btpres_par_O2_2_btaire_cupula_btpeso_btph_1_btph_2_btantiespumante_bttotal_antiespumante_btsol_base_bttotal_sol_base_btpres_parcial_O2_btph_cultivo_bttemp_btid_bio
4717072024-09-10 19:45:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.37039914618
4717082024-09-10 20:00:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.27294614618
4717092024-09-10 20:15:00+00:000.00.0480.00.00.00.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.39432414618
4717102024-09-10 20:30:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.27525814618
4717112024-09-10 20:45:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.23199514618
4717122024-09-10 21:00:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.35300314618
4717132024-09-10 21:15:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.25111714618
4717142024-09-10 21:30:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.23938314618
4717152024-09-10 21:45:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.22473814618
4717162024-09-10 22:00:00+00:000.00.0480.00.0NaN0.0-6.241.248973-0.3424310.029.7600010.00.0735.895508800.0399915.21361414618